Using AI Agents in Learning and Development: Your Questions Answered

The landscape of learning and development (L&D) has experienced a seismic shift with the advent of artificial intelligence (AI). While AI has opened doors to faster course creation, localization, and publishing, professionals are still grappling with practical ways to utilize these tools effectively. With the introduction of AI Agents, L&D pros are also navigating how to add these digital teammates to their current processes as a way to get more done while keeping quality intact.

In this article, we answer some of the most pressing questions raised by L&D professionals today, drawing insights from the recent webinar, From Prompt to Published: How AI Agents Can Automate Your L&D Life, hosted by Debbie Richards, Chief Learning Officer at Cognota and President Emeritus of ATD Houston, and Genevieve Carbone, Product Marketing Director for L&D at Smartcat.

• Generative AI speeds up content creation but doesn’t fix L&D’s broader workflow challenges like formatting, localization, and publishing.

• AI Agents automate entire end-to-end learning workflows, accelerating both content creation and delivery across multiple languages.

• L&D teams should start small with one repeatable workflow to prove value and then scale automation efforts across the organization.

• By acting as digital teammates, AI Agents reduce manual work, enhance collaboration, and link learning outcomes directly to business impact.

Generative AI tools, such as text generation platforms, are undoubtedly capable of creating course outlines, scripts, and content faster than ever before. However, these tools often fall short in providing holistic solutions for L&D workflows. As Debbie Richards, an expert in learning innovation, explains:

“You might use an AI tool to write a course outline with AI, but then you are manually importing that into your authoring tool, applying formatting, dealing with all the different templates and things. And then comes the translation. So if you have to do translation for that course, you sometimes will take the output from that course and then send it via email or a shared doc to reviewers. Things start to slow down, and sometimes they break down as well. It’s like AI has given us a jump start, but we haven’t gotten closer to that finish line.”

Rather than accelerating the overall process, generative AI tools often shift the friction to other stages of the workflow. Debbie adds:

"It's like AI has given us a jump start, but we haven't gotten closer to that finish line."

L&D professionals need solutions that address not only content creation but also localization, formatting, and publishing to truly achieve scalable workflows.

AI agents are designed to provide end-to-end automation in L&D, functioning as project executors that handle multiple tasks seamlessly. Genevieve Carbone, a strategist with experience in messaging optimization, emphasizes the transformative nature of these agents:

“AI Agents aren’t here to save you time on just one task—they’re here to accelerate the entire outcome. You can give them a goal, like building a module and delivering it in five languages, and they’ll handle everything in between. You’re not pushing the workflow forward anymore; the agents are the workflow.”

Imagine a scenario where a subject matter expert submits a single draft, and, by the end of the day, a polished course is published in multiple languages—AI agents make this future possible. Debbie elaborates:

By consolidating tasks such as file formatting and translation, AI agents transform messy, multi-tool workflows into streamlined, intuitive processes that prioritize speed and consistency.

Traditional workflows often involve a fragmented series of tools and manual steps, leaving teams bogged down by inefficiencies. Debbie uses an example to illustrate this point:

“The old way of working—with disconnected tools and constant back-and-forth between teams—isn’t fixed by adding AI to one step. The process still breaks down if it isn’t connected end to end.”

In contrast, AI agents streamline these processes by centralizing tasks within a single platform: "You're going from a dozen different tools to managing a single output."

This shift not only saves time but also reduces the likelihood of errors and miscommunication, enabling teams to focus on strategic aspects of learning design.

Enterprise organizations often have unique requirements, such as strict security measures, multilingual content needs, and high scalability demands. AI agents are designed specifically to address these challenges. According to Genevieve:

"The agents are in a secure environment, and everything has an audit trail enabled. All of your data is going to stay within your domain."

Debbie further underscores the enterprise focus of AI agents:

"They're not trying to be everything; they are specifically for L&D tasks. You don't have to train them from scratch. They already know how to structure a learning module, and they'll generate content in multiple languages."

These features make AI agents an ideal fit for enterprise teams needing reliable, scalable, and secure solutions.

The key to successful AI adoption lies in starting small and scaling efforts. Debbie suggests piloting a single workflow that’s repeatable and high-value, like converting a PDF into a course. This approach minimizes risk while demonstrating proof of concept. Debbie explains:

“Start small. Pick one workflow you can test—something repeatable and high-value, like converting a PDF into a course. Use that to prove the value. Once you see results, you can scale from there. It’s not about doing everything at once; it’s about building confidence and showing impact early.”

Genevieve also highlights how AI agents can provide immediate benefits even at the initial stages:

"You're automating the results and the outcome. AI agents can become part of your team."

A pilot project enables teams to build familiarity with these agents while showcasing measurable outcomes to stakeholders.

AI agents excel at minimizing repetitive tasks that often bog down L&D teams, allowing professionals to focus on higher-value responsibilities. Genevieve Carbone shared a case study involving a global pharmaceuticals company, where subject matter expert workload was reduced by 70%:

“Even in early pilots, teams see measurable results right away—time saved, translation costs reduced, and fewer bottlenecks. One global team we worked with cut SME workload by 70% and translation costs by the same margin, all while improving consistency across regions. That’s the kind of operational lift AI Agents can bring.”

Another example involved a manufacturing company that streamlined multilingual training for product launches. Genevieve noted:

"They were able to cut the translation costs by 70% while maintaining a really high quality."

Eliminating these bottlenecks not only saves time and costs but also ensures better alignment between training delivery and organizational goals.

Localization is a critical component for global L&D programs, and AI agents simplify the process by automating translations and adapting content for different regions. Debbie highlights the efficiency of this approach:

“The agent translates all of the content, prepares ready-to-publish files, and structures everything for the LMS. Whether it’s three languages or twenty, the process is the same—consistent, fast, and reliable.”

Whether teams need training materials in 3 languages or 20, AI agents ensure high-quality translations without added complexity.

Beyond automating tasks, AI agents foster better collaboration among teams by acting as intuitive “digital teammates.” Genevieve explained this concept:

“AI Agents are not just tools. They’re like built-in teammates that handle the heavy lifting inside your workflow. They make it possible for L&D teams to move from doing everything manually to actually orchestrating learning at scale. That’s what changes the game—not the prompt, but the process.”

Debbie Richards also stresses the importance of providing AI agents with clear goals:

“Agents work best when you give them goals, not prompts. The clearer you are about what success looks like, the better they’ll perform. It’s a collaboration—you’re not replacing people; you’re teaching the agent how to work alongside them.”

This human-centered interaction design ensures agents can effectively support teams while fostering trust in AI-driven processes.

AI agents represent a paradigm shift for the learning and development industry by offering scalable, efficient solutions that streamline the entire workflow—from creation to localization and publishing. By saving time, reducing workload, and ensuring consistency, they empower teams to deliver impactful training faster. Whether you’re just beginning to explore AI tools or already testing automation, consider piloting AI agents to uncover their potential.

“We need to stop seeing AI as just a shiny object and start looking at the business outcomes it supports. It’s not about using AI for the sake of using it—it’s about improving speed, consistency, and the learner experience. That’s how we show real value as L&D leaders.” - Debbie Richards

Smartcat Agents are specifically designed to meet the demanding requirements of enterprise learning and development. With their secure infrastructure, multilingual capabilities, and intuitive features, Smartcat Agents are transforming how global teams create and deliver training programs. Whether it’s automating multilingual localization, creating microlearning courses, or scaling enterprise-wide training, Smartcat Agents integrate seamlessly into your workflows, helping you save time, reduce costs, and focus on delivering impactful learning solutions.